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We consider a team of heterogeneous robots which are deployed within a commonworkspace to gather different types of data. The robots have different rolesdue to different capabilities: some gather data from the workspace (sourcerobots) and others receive data from source robots and upload them to a datacenter (relay robots). The data-gathering tasks are specified locally to eachsource robot as high-level Linear Temporal Logic (LTL) formulas, that capturethe different types of data that need to be gathered at different regions ofinterest. All robots have a limited buffer to store the data. Thus the datagathered by source robots should be transferred to relay robots before theirbuffers overflow, respecting at the same time limited communication range forall robots. The main contribution of this work is a distributed motioncoordination and intermittent communication scheme that guarantees thesatisfaction of all local tasks, while obeying the above constraints. The robotmotion and inter-robot communication are closely coupled and coordinated duringrun time by scheduling intermittent meeting events to facilitate the local planexecution. We present both numerical simulations and experimental studies todemonstrate the advantages of the proposed method over existing approaches thatpredominantly require all-time network connectivity.

Multi-Robot Data Gathering Under Buffer Constraints and Intermittent Communication